干旱区生态环境知识资源中心(Arid): Detecting Irrigation Events over Semi-Arid and Temperate Climatic Areas Using Sentinel-1 Data: Case of Several Summer Crops

Arid

DOI	10.3390/agronomy12112725
	Detecting Irrigation Events over Semi-Arid and Temperate Climatic Areas Using Sentinel-1 Data: Case of Several Summer Crops
	Bazzi, Hassan; Baghdadi, Nicolas; Najem, Sami; Jaafar, Hadi; Le Page, Michel; Zribi, Mehrez; Faraslis, Ioannis; Spiliotopoulos, Marios
通讯作者	Bazzi, H ; Baghdadi, N
来源期刊	AGRONOMY-BASEL
EISSN	2073-4395
出版年	2022
卷号	12 期号:11
英文摘要	Irrigation monitoring is of great importance in agricultural water management to guarantee better water use efficiency, especially under changing climatic conditions and water scarcity. This study presents a detailed assessment of the potential of the Sentinel-1 (S1) Synthetic Aperture Radar (SAR) data to detect irrigation events at the plot scale. The potential of the S1 data to detect the irrigation events was carried out using the Irrigation Event Detection Model (IEDM) over semi-arid and temperate oceanic climates in five study sites in south Europe and the Middle East. The IEDM is a decision tree model initially developed to detect irrigation events using the change detection algorithm applied to the S1 time series data. For each study site and at each agricultural plot, all available S1 images during the period of irrigation were used to construct an S1 time series and apply the IEDM. Different types of major summer irrigated crops were analyzed in this study, including Maize, Soybean, Sorghum and Potato, mainly with the sprinkler irrigation technique. The irrigation detection accuracy was evaluated using S1 images and the IEDM against the climatic condition of the studied area, the vegetation development (by means of the normalized difference vegetation index, NDVI) and the revisit time of the S1 sensor. The main results showed generally good overall accuracy for irrigation detection using the S1 data, reaching 67% for all studied sites together. This accuracy varied according to the climatic conditions of the studied area, with the highest accuracy for semi-arid areas and lowest for temperate areas. The analysis of the irrigation detection as a function of the crop type showed that the accuracy of irrigation detection decreases as the vegetation becomes well developed. The main findings demonstrated that the density of the available S1 images in the S1 time series over a given area affects the irrigation detection accuracy, especially for temperate areas. In temperate areas the irrigation detection accuracy decreased from 70% when 15 to 20 S1 images were available per month to reach less than 56% when less than 10 S1 images per month were available over the study sites.
英文关键词	remote sensing precision agriculture sustainability climate change
类型	Article
语种	英语
开放获取类型	Green Published, gold
收录类别	SCI-E
WOS记录号	WOS:000886115500001
WOS关键词	INTEGRAL-EQUATION MODEL ; SOIL-MOISTURE RETRIEVAL ; TIME-SERIES ; SAR DATA ; C-BAND ; RADAR ; AGRICULTURE ; METHODOLOGY ; CALIBRATION ; FOOD
WOS类目	Agronomy ; Plant Sciences
WOS研究方向	Agriculture ; Plant Sciences
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/391781
推荐引用方式 GB/T 7714	Bazzi, Hassan,Baghdadi, Nicolas,Najem, Sami,et al. Detecting Irrigation Events over Semi-Arid and Temperate Climatic Areas Using Sentinel-1 Data: Case of Several Summer Crops[J],2022,12(11).
APA	Bazzi, Hassan.,Baghdadi, Nicolas.,Najem, Sami.,Jaafar, Hadi.,Le Page, Michel.,...&Spiliotopoulos, Marios.(2022).Detecting Irrigation Events over Semi-Arid and Temperate Climatic Areas Using Sentinel-1 Data: Case of Several Summer Crops.AGRONOMY-BASEL,12(11).
MLA	Bazzi, Hassan,et al."Detecting Irrigation Events over Semi-Arid and Temperate Climatic Areas Using Sentinel-1 Data: Case of Several Summer Crops".AGRONOMY-BASEL 12.11(2022).